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Power outage is one of the significant problems for electricity distribution companies. Power outages cause customer dissatisfaction and reduce distribution companies' profits and revenues. Therefore, the electricity distribution companies are trying to moderate the leading causes of the outage. However, the dynamics of environmental conditions cre...
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... in cut-out fuse 2-Work in network limit zone 3-Modification and optimization of the network 4-Unfavorable weather conditions 5-Fault in the transformer 6-Collision of external objects, birds, and annoying trees 7-Fault in the jumper 8-Other causes. A comparison of the best outage criterion with other criteria in the first scenario is presented in Table 2. In this study, among the criteria related to outages and macro-level operational plans, two key factors affect their prioritization with high uncertainty: 1) The economic conditions of the company and society, 2) weather and environmental conditions. ...Similar publications
TOPSIS is a well-known approach applied to multi-criteria decision-making under certainty (M-DMC). However, recently, some analogies between this domain and scenario-based one-criterion decision-making under uncertainty (1-DMU) have been revealed in the literature. Thus, the similarities aforementioned give the possibility to adjust TOPSIS to anoth...
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... Moreover, Mahmood et al. [36] presented the Aczel-Alsina operators for BCFSs. Further, some fundamental techniques and methods are described in the following, for instance, Schweizer-Sklar operators [37], the VIKOR technique [38], the SWARA-COPRAS technique [39], renewable energy resources [40], a best-worst technique [41], decision-making technique [42], DEMATEL-ISM integration method [43], IFSs and their applications [44], BHARAT decision-making model [45], Hamy mean operators [46], Aczel-Alsina operators [47], analysis of decision accuracy in DEMATEL technique [48], Einstein operators [49], MADM technique based on vague sets [50], Bonferroni mean operators [51], decision-making strategy [52,53], fuzzy soft code [54], Fermatean fuzzy sets [55], analysis of convexity based on hyper-soft sets [56], Pythagorean fuzzy linear programming [57], analysis of hybrid model based on IFS [58], the parsimonious spherical fuzzy sets [59,60], the AHP model [61], linear programming [62] and the aggregation operators [63]. ...
The model of bipolar complex fuzzy linguistic set is a very famous and dominant principle to cope with vague and uncertain information. The bipolar complex fuzzy linguistic set contained the positive membership function, negative membership function, and linguistic variable, where the technique of fuzzy sets to bipolar fuzzy sets are the special cases of the bipolar complex fuzzy linguistic set. In this manuscript, we describe the model of Aczel-Alsina operational laws for bipolar complex fuzzy linguistic values based on Aczel-Alsina t-norm and Aczel-Alsina t-conorm. Additionally, we compute the Aczel-Alsina power aggregation operators based on bipolar complex fuzzy linguistic data, called bipolar complex fuzzy linguistic Aczel-Alsina power averaging operator, bipolar complex fuzzy linguistic Aczel-Alsina power weighted averaging operator, bipolar complex fuzzy linguistic Aczel-Alsina power geometric operator, and bipolar complex fuzzy linguistic Aczel-Alsina power weighted geometric operator with some dominant and fundamental laws such as idempotency, monotonicity, and boundedness. Moreover, we initiate the model of the Weighted Aggregates Sum Product Assessment technique with the help of consequent theory. In the context of geographic information systems and spatial information systems, coupling aims to find out the relationships among different components within a geographic information system, where coupling can occur at many stages, for instance, spatial coupling, data coupling, and functional coupling. To evaluate the above dilemma, we perform the model of multi-attribute decision-making for invented operators to compute the best technique for addressing geographic information systems. In the last, we deliberate some numerical examples for comparing the ranking results of proposed and prevailing techniques.
... In the decision analysis section, this paper uses the entropy-based Topsis method [84][85][86][87][88][89][90][91][92][93] when making decisions on the optimization scheme. The method has the following advantages: The entropy weighting method can confirm the weighting information of the target indicators by analyzing the entropy value of the target indicators of each scenario, which in turn can provide a reference for the multi-objective assessment later. ...
The White Paper on Peak Carbon and Carbon Neutral Action 2022 states that China is to achieve peak carbon by 2030 and carbon neutrality by 2060. Based on the “3060 dual-carbon” goal, how to improve the efficiency of energy performance is an important prerequisite for building a low-carbon, energy-saving, green, and beautiful China. The office performance building studied in this paper is located in the urban area of Turpan, where the climate is characterized by an extremely hot summer environment and a cold winter environment. At the same time, the building is oriented east–west, with the main façade facing west, and the main façade consists of a large area of single-layer glass curtain wall, which is affected by western sunlight. As a result, there are serious problems with the building’s energy consumption, which in turn leads to excessive carbon emissions and high life cycle costs for the building. To address the above problems, this paper analyzes and optimizes the following four dimensions. First, the article creates a Convolutional Neural Network (CNN) prediction model with Total Energy Use in Buildings (TEUI), Global Warming Potential (GWP), and Life Cycle Costs (LCC) as the performance objectives. After optimization, the R² of the three are 0.9908, 0.9869, and 0.9969, respectively, thus solving the problem of low accuracy of traditional prediction models. Next, the NSGA-II algorithm is used to optimize the three performance objectives, which are reduced by 41.94%, 40.61%, and 31.29%, respectively. Then, in the program decision stage, this paper uses two empowered Topsis methods to optimize this building performance problem. Finally, the article analyzes the variables using two sensitivity analysis methods. Through the above research, this paper provides a framework of optimization ideas for office buildings in extremely hot and cold regions while focusing on the four major aspects of machine learning, multi-objective optimization, decision analysis, and sensitivity analysis systematically and completely. For the development of office buildings in the region, whether in the early program design or in the later stages, energy-saving measures to optimize the design have laid the foundation of important guidelines.
... BWM presents a method rooted in pairwise comparisons for addressing MCDM problems (Rezaei 2015). This approach was developed to overcome the shortcomings, such as inconsistency, observed in multi-criteria decision-making techniques that depend on matrices for pairwise comparisons (Shahi Moridi et al. 2023). The BWM method establishes weights for a group of decision criteria by comparing the best and worst criteria with all others through a binary assessment (Ghanbari ). ...
Sustainable competitive advantage, a cornerstone of strategic management, encompasses a business's enduring capability to maintain long-term financial superiority over its competitors. The business should optimize its operations by reducing costs and improving efficiency to attain a sustainable competitive advantage. In the present study, the Activity-Based Costing (ABC) system was implemented to calculate the unit costs of a hotel operating in Turkey, and the expenses were allocated to the overnight costs using the Full-Consistency Method (FUCOM) technique. FUCOM is designed to determine room costs in a hotel business accurately. Expert evaluations were simulated to interpret the results statistically. Also, the Best–worst method (BWM) is used to compare the results. The results of this study hold significant implications for decision-makers, implementers, stakeholders, and theoretical contributions to hotel operations. The proposed model will enable hotels to identify room costs and realistically achieve a sustainable competitive edge. The proposed system is also suitable for implementation by other enterprises operating in the service sector.
... There are various mathematical techniques that can be classified as MCDM methods and used for irrigation district evaluation, such as the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) [20], Bayesian Network (BN) models [21], Data Envelopment Analysis (DEA) [22], the Variable Fuzzy Set (VFS) [23], the Weighted Average Method [24], the Project Pursuit Model [25], VIse Kriterijumski Optimizacioni Racun (VIKOR) [26], and the Best-Worst Method (BWM) [27]. Among these methods, TOPSIS is a decisionmaking technique for multiple-objective decision analysis that was proposed by Hwang and Yoon [28,29] and has been successfully applied in many fields, including, but not limited to, electrical network management [30], assessments [31,32], human resource management [33], supplier selection [34], and carbon regulation [35,36]. Here, an emphasis is placed on the quantifiable difference between the evaluation object's state at a specific time and the ideal state, which can be effectively handled by TOPSIS [37,38]. ...
Irrigation districts are a pivotal infrastructure of agricultural water conservancy engineering. Implementing modernization will be the main task of large-scale irrigation districts for a considerable amount of time in the future. In this study, four typical large-scale irrigation districts in North China were investigated: the Renmin Shengliqu, Weishan, Shijin, and Zuncun irrigation districts. The concept of a modern irrigation district was deconstructed to establish an evaluation index system which includes four second-level indicators, twelve third-level indicators, and thirty fourth-level indicators. A hybrid approach based on AHP and OWA was used to quantify indicator weights used in group decision making. TOPSIS was introduced to measure the modernization level of the four irrigation districts. An obstacle factor diagnosis model was applied to search for key obstacle factors that will affect the modernization and improvement of the irrigation districts. The results showed that (1) the modernization levels of the Renmin Shengliqu, Weishan, Shijin, and Zuncun irrigation districts in 2020 and 2025 were 0.3916 and 0.5755, 0.3748 and 0.5396, 0.4493 and 0.6012, and 0.2343 and 0.6166, respectively. The evaluation results indicate that the four irrigation districts are still in the beginning phase (or even preparation phase) of the modernization process. (2) Eight indicators were identified as the main common obstacle factors for the four evaluated irrigation districts, including the irrigation water-use efficiency factor, the coverage proportion of information technology, the proportion of efficient water conservation irrigation areas, and so on. (3) There are two effective methods to enhance the modernization level of the four irrigation districts: improving water resource utilization efficiency and strengthening the management system with an emphasis on informatization. The present study can enrich the theoretical evaluation of irrigation districts and provide a scientific basis for the modernized construction and management of irrigation districts in China.
... In addition to this, this paper uses the entropy-based TOPSIS method when making multi-objective decisions on multiple scenarios [38][39][40][41][42][43][44][45][46][47][48]. The methodology used has the following advantages when performing the analysis: The entropy weight method can determine the weight of the indicators by calculating the information entropy of each indicator, and then provide a basis for multi-objective evaluation. ...
... Moridi et al. went on to improve the bad effects of blackouts by studying the factors that affect them. The article analyzes the influencing factors through the best-worst and TOPSIS methods, and the results show that working in grid-restricted areas is the main cause of power outages in urban areas [39]. Liu et al. went on to explore the influence of wind environment factors in building design by investigating the optimal wind environment for building complexes in different seasons. ...
China is committed to reaching peak carbon by 2030 and carbon neutrality by 2060. The goals of reducing energy consumption and building a “beautiful China” are being urgently pursued in China. The building studied in this paper is located in the city of Turpan, where the problem of excessive energy use among buildings is significant due to the region’s hot summers and cold winters. Additionally, the fact that the office building studied in this paper has an east–west orientation is significant: the building’s main façade is oriented to the west, comprising a large area of single-layer glass curtain wall. Based on this, this paper proposes optimization strategies from two perspectives of renovation and new construction. Four design options are proposed at the retrofit level: glazed circular curtain wall; glazed enclosed curtain wall; west-facing double-glazed curtain wall circulation combined with south-facing light from the east; recycling of windows on the inside of the exterior glass curtain wall. These suggestions focus on retrofitting the glass curtain wall on the west elevation of the building. Two design options are proposed at the new-build level: west-facing south-oriented light and west-facing north-oriented light. These suggestions were primarily built around the idea of changing the orientation of the windows on the west elevation. The results show that the optimal solution is to implement the west-facing double-glazed curtain wall circulation combined with south-facing light from the east. This program shows a 64.14% reduction in heating energy consumption, a 77.12% reduction in cooling energy consumption, and a 69.67% reduction in total energy consumption. The above research has improved the deficiencies in the performance-based energy efficiency retrofit of office buildings in the region and provided new ideas and suggestions for policymakers and designers to build energy-efficiency retrofits in the early stages.
... As vision technology develops, AIML is incorporated into the anticipated system model to mitigate risky aspects of monitoring settings. The front end of an AIML system performs dependent functions, while the rear end is employed for independent functions thanks to a connection between two processing units [20][21][22][23][24][25][26][27][28]. Equation (14) is used to detect the motion of unmanned aircraft in AIML. ...
In this study, unidentified flying machines are built with real-time monitoring in mid-course settings for obstacle avoidance in mind. The majority of the currently available methods are implemented as comprehensive monitoring systems, with significant success in monitored applications like bridges, railways, etc. So, the predicted model is developed exclusively for specific monitoring settings, as opposed to the broad conditions that are used by the current approaches. Also, in the design model, the first steps are taken by limiting the procedure to specific heights, and the input thrust that is provided for take up operation is kept to a minimum. Due to the improved altitudes, the velocity and acceleration units have been cranked up on purpose, making it possible to sidestep intact objects. In addition, Advanced Image Mapping Localization (AIML) is used to carry out the implementation process, which identifies stable sites at the correct rotation angle. Besides, Cyphal protocol integration improves the security of the data-gathering process by transmitting information gathered from sensing devices. The suggested system is put to the test across five different case studies, where the designed Unmanned aerial vehicle can able to detect 25 obstacles in the narrow paths in considered routs but existing approach can able to identify only 14 obstacle in the same routes.
Cloud Computing has gained substantial popularity due to its ability to offer diverse and dependable computing services suited to clients demands. Given the rapid expansion of this technology, an increasing number of IT service providers are competing to deliver cloud services that are both of excellent quality and cost-efficient, in order to best meet the requirements of their clients. With the extensive range of options available, selecting the best Cloud Service Provider (CSP) has become a challenging dilemma for the majority of cloud clients. When evaluating services offered by many CSPs, it is important to consider multiple attributes. Efficiently addressing the selection of the best CSP involves tackling a challenging Multi-Attribute Decision Making (MADM) problem. Several MADM techniques have been proposed in academic literature for evaluating CSPs. However, the persisting problems of inconsistency, uncertainty, and rank reversal remain unresolved. In this paper the authors present a hybrid MADM framework to rank eight CSPs using nine Quality of Service (QoS) attributes. In order to achieve this objective, Fermatean fuzzy sets-full consistency method (FFS-FUCOM) is combined with Grey-Relational-Analysis and the Technique-for-Order-Preference-by-Similarity-to-Ideal-Solution (Grey-TOPSIS) technique. The framework successfully resolved the A. K. Al-Mashhadani, et al. / Quality of Service Attributes 2 aforementioned problems. Sensitivity analysis is conducted to assess the stability and robustness of the results produced by the proposed framework. The sensitivity analysis results indicate that the proposed framework offers an accurate and robust solution. A systematic ranking test is undertaken to ensure that the results are ranked in a systematic manner. Additionally, a comparative analysis is carried out with the most relevant study.
Cloud Computing has gained substantial popularity due to its ability to offer diverse and dependable computing services suited to clients demands. Given the rapid expansion of this technology, an increasing number of IT service providers are competing to deliver cloud services that are both of excellent quality and cost-efficient, in order to best meet the requirements of their clients. With the extensive range of options available, selecting the best Cloud Service Provider (CSP) has become a challenging dilemma for the majority of cloud clients. When evaluating services offered by many CSPs, it is important to consider multiple attributes. Efficiently addressing the selection of the best CSP involves tackling a challenging Multi-Attribute Decision Making (MADM) problem. Several MADM techniques have been proposed in academic literature for evaluating CSPs. However, the persisting problems of inconsistency, uncertainty, and rank reversal remain unresolved. In this paper the authors present a hybrid MADM framework to rank eight CSPs using nine Quality of Service (QoS) attributes. In order to achieve this objective, Fermatean fuzzy sets-full consistency method (FFS-FUCOM) is combined with Grey-Relational-Analysis and the Technique-for-Order-Preference-by-Similarity-to-Ideal-Solution (Grey-TOPSIS) technique. The framework successfully resolved the aforementioned problems. Sensitivity analysis is conducted to assess the stability and robustness of the results produced by the proposed framework. The sensitivity analysis results indicate that the proposed framework offers an accurate and robust solution. A systematic ranking test is undertaken to ensure that the results are ranked in a systematic manner. Additionally, a comparative analysis is carried out with the most relevant study.
